easy-rag/services/rag_service.py

117 lines
3.8 KiB
Python

from typing import List, Dict, Any
import asyncio
from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
from services.vector_store import AsyncVectorStore
import os
import time
class AsyncRAGService:
"""异步 RAG 服务主类"""
def __init__(self):
self.vector_store = AsyncVectorStore()
self.llm = ChatOpenAI(
model="deepseek-r1:8b",
temperature=0.7,
openai_api_key=os.getenv("OPENAI_API_KEY"),
openai_api_base=os.getenv("OPENAI_BASE_URL"),
)
self.prompt_template = PromptTemplate(
input_variables=["context", "question"],
template="""
基于以下上下文回答问题。如果上下文中没有相关信息,请说明无法从提供的文档中找到答案。
上下文:
{context}
问题:{question}
答案:""",
)
async def add_document_async(self, content: str, filename: str) -> str:
"""异步添加文档"""
return await self.vector_store.add_document_async(content, filename)
async def chat_async(
self, question: str, top_k: int = 3, temperature: float = 0.7
) -> Dict[str, Any]:
"""异步聊天问答"""
start_time = time.time()
# 异步检索相关文档
search_results = await self.vector_store.search_async(question, top_k)
if not search_results:
return {
"answer": "抱歉,我无法在现有文档中找到相关信息来回答您的问题。",
"sources": [],
"processing_time": time.time() - start_time,
}
# 并行执行上下文构建和 LLM 调用准备
context_task = asyncio.create_task(self._build_context_async(search_results))
sources_task = asyncio.create_task(self._format_sources_async(search_results))
# 等待上下文构建完成
context = await context_task
# 异步生成回答
self.llm.temperature = temperature
prompt = self.prompt_template.format(context=context, question=question)
response = await asyncio.to_thread(self.llm.invoke, prompt)
# 等待源信息格式化完成
sources = await sources_task
return {
"answer": response.content,
"sources": sources,
"processing_time": time.time() - start_time,
}
async def get_documents_async(self) -> List[Dict[str, Any]]:
"""异步获取文档列表"""
return await self.vector_store.get_documents_async()
async def delete_document_async(self, doc_id: str) -> bool:
"""异步删除文档"""
return await self.vector_store.delete_document_async(doc_id)
async def _build_context_async(self, search_results: List[Dict[str, Any]]) -> str:
"""异步构建上下文"""
def _build_context():
return "\n\n".join(
[
f"文档片段 {i+1} (来源: {result['metadata']['filename']}):\n{result['content']}"
for i, result in enumerate(search_results)
]
)
return await asyncio.to_thread(_build_context)
async def _format_sources_async(
self, search_results: List[Dict[str, Any]]
) -> List[Dict[str, Any]]:
"""异步格式化源信息"""
def _format_sources():
return [
{
"filename": result["metadata"]["filename"],
"content": (
result["content"][:200] + "..."
if len(result["content"]) > 200
else result["content"]
),
"similarity": 1 - result["distance"],
}
for result in search_results
]
return await asyncio.to_thread(_format_sources)